Upsert data into Azure Cosmos DB for Apache Cassandra from Spark

Članek
08/14/2024

APPLIES TO: Cassandra

This article describes how to upsert data into Azure Cosmos DB for Apache Cassandra from Spark.

API for Cassandra configuration

Set below spark configuration in your notebook cluster. It's one time activity.

//Connection-related
 spark.cassandra.connection.host  YOUR_ACCOUNT_NAME.cassandra.cosmosdb.azure.com  
 spark.cassandra.connection.port  10350  
 spark.cassandra.connection.ssl.enabled  true  
 spark.cassandra.auth.username  YOUR_ACCOUNT_NAME  
 spark.cassandra.auth.password  YOUR_ACCOUNT_KEY  
// if using Spark 2.x
// spark.cassandra.connection.factory  com.microsoft.azure.cosmosdb.cassandra.CosmosDbConnectionFactory  

//Throughput-related...adjust as needed
 spark.cassandra.output.batch.size.rows  1  
// spark.cassandra.connection.connections_per_executor_max  10   // Spark 2.x
 spark.cassandra.connection.remoteConnectionsPerExecutor  10   // Spark 3.x
 spark.cassandra.output.concurrent.writes  1000  
 spark.cassandra.concurrent.reads  512  
 spark.cassandra.output.batch.grouping.buffer.size  1000  
 spark.cassandra.connection.keep_alive_ms  600000000

Note

If you are using Spark 3.x, you do not need to install the Azure Cosmos DB helper and connection factory. You should also use remoteConnectionsPerExecutor instead of connections_per_executor_max for the Spark 3 connector (see above).

Warning

The Spark 3 samples shown in this article have been tested with Spark version 3.2.1 and the corresponding Cassandra Spark Connector com.datastax.spark:spark-cassandra-connector-assembly_2.12:3.2.0. Later versions of Spark and/or the Cassandra connector may not function as expected.

Dataframe API

Create a dataframe

import org.apache.spark.sql.cassandra._
//Spark connector
import com.datastax.spark.connector._
import com.datastax.spark.connector.cql.CassandraConnector

//if using Spark 2.x, CosmosDB library for multiple retry
//import com.microsoft.azure.cosmosdb.cassandra

// (1) Update: Changing author name to include prefix of "Sir"
// (2) Insert: adding a new book

val booksUpsertDF = Seq(
    ("b00001", "Sir Arthur Conan Doyle", "A study in scarlet", 1887),
    ("b00023", "Sir Arthur Conan Doyle", "A sign of four", 1890),
    ("b01001", "Sir Arthur Conan Doyle", "The adventures of Sherlock Holmes", 1892),
    ("b00501", "Sir Arthur Conan Doyle", "The memoirs of Sherlock Holmes", 1893),
    ("b00300", "Sir Arthur Conan Doyle", "The hounds of Baskerville", 1901),
    ("b09999", "Sir Arthur Conan Doyle", "The return of Sherlock Holmes", 1905)
    ).toDF("book_id", "book_author", "book_name", "book_pub_year")
booksUpsertDF.show()

Upsert data

// Upsert is no different from create
booksUpsertDF.write
  .mode("append")
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks"))
  .save()

Update data

//Cassandra connector instance
val cdbConnector = CassandraConnector(sc)

//This runs on the driver, leverage only for one off updates
cdbConnector.withSessionDo(session => session.execute("update books_ks.books set book_price=99.33 where book_id ='b00300' and book_pub_year = 1901;"))

RDD API

Note

Upsert from the RDD API is same as the create operation

Next steps

Proceed to the following articles to perform other operations on the data stored in Azure Cosmos DB for Apache Cassandra tables:

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